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Updated: Jul 27, 2025

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rang: Reconstructing reproducible R computational environments.

Chung-Hong Chan1, David Schoch1

  • 1GESIS Leibniz-Institut für Sozialwissenschaften, Mannheim, Germany.

Plos One
|June 8, 2023
PubMed
Summary
This summary is machine-generated.

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The R package rang ensures computational reproducibility by creating declarative descriptions of research environments. This enables the reconstruction of past computational environments, making old code executable again.

Area of Science:

  • Computational science
  • Data science
  • Software engineering

Background:

  • Computational reproducibility is often hindered by missing descriptions of the software environment.
  • Software obsolescence and missing system components can prevent future execution of research code.

Purpose of the Study:

  • To introduce the R package rang as a solution for generating declarative descriptions of computational environments.
  • To enable automatic reconstruction of specific computational environments for enhanced reproducibility.
  • To facilitate the creation and sharing of reproducible research compendia.

Main Methods:

  • Utilizing the R package rang to generate a declarative description of the computational environment.
  • Employing Docker for the automated reconstruction of the computational environment.

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  • Testing the reconstruction process with R code dating back to 2001.

    • Main Results:

    • The rang package successfully generates declarative descriptions that meet the criteria for reproducible research compendia.
    • The Docker-based reconstruction process proved effective for R code from 2001 onwards.
    • rang enables the re-execution of previously unexecutable code from diverse fields.

    Conclusions:

    • The rang package provides a comprehensive solution for achieving computational reproducibility.
    • Researchers can use rang to create and share reproducible research compendia, ensuring long-term accessibility of their work.
    • rang is available on CRAN and GitHub.